What is a time series?

“a series of values of a quantity obtained at successive times, often with equal intervals between them”

What is a time series?

# A tibble: 100 × 2
       t value
   <int> <dbl>
 1     1     5
 2     2     5
 3     3     3
 4     4     4
 5     5     4
 6     6     4
 7     7     4
 8     8     3
 9     9     3
10    10     2
11    11     3
12    12     4
13    13     4
14    14     3
15    15     3
# … with 85 more rows

Who should care about time series?

People who:

• study longitudinal change (e.g., development)

• study variability (e.g., experience sampling, passive sensing)

• run experiments with multiple trials

• study cohort or age differences

• simulations (e.g., trace plots in bayesian models)

• Time is everywhere, and ignoring it can be problematic

What will we cover with time series:

• Univariate time series
  
• Multivariate time series
  
• Connected scatter plots
• Smoothing
• Detrended time series

Quick clarification: Time Series v Trends

• Trends can mean many things, from autocorrelation to mean-level change
• However, in psychology, we often think of trends as patterns of normative longitudinal change
• This is fine usage, but trends don’t have be linear / curvilinear increases / decreases
  • seasonal trends
  • cohort effects
  • etc. are all trends, too

Univariate and Multivariate Time Series

Univariate and Multivariate Time Series

• How you visualize the trends you are trying to uncover in a time series will depend on the research question you are asking
  • e.g., very basic time series visualizations are great for descriptives
  • But to include it in a presentation / papers, we usually want to add more affordances that clarify nothing went wrong
  • Affordances include, text, shading, and more, in aligment with Gestalt principles and how we process different aspects of visualizations